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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Computational Identification of Small Interfering RNA Targets in SARS-CoV-2</title><author><name sortKey="Chen, Wei" sort="Chen, Wei" uniqKey="Chen W" first="Wei" last="Chen">Wei Chen</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.411304.3</institution-id><institution-id institution-id-type="ISNI">0000 0001 0376 205X</institution-id><institution>Innovative Institute of Chinese Medicine and Pharmacy,</institution><institution>Chengdu University of Traditional Chinese Medicine,</institution></institution-wrap>Chengdu, 611137 China</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Feng, Pengmian" sort="Feng, Pengmian" uniqKey="Feng P" first="Pengmian" last="Feng">Pengmian Feng</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.411304.3</institution-id><institution-id institution-id-type="ISNI">0000 0001 0376 205X</institution-id><institution>Innovative Institute of Chinese Medicine and Pharmacy,</institution><institution>Chengdu University of Traditional Chinese Medicine,</institution></institution-wrap>Chengdu, 611137 China</nlm:aff></affiliation></author><author><name sortKey="Liu, Kewei" sort="Liu, Kewei" uniqKey="Liu K" first="Kewei" last="Liu">Kewei Liu</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Wu, Meng" sort="Wu, Meng" uniqKey="Wu M" first="Meng" last="Wu">Meng Wu</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Lin, Hao" sort="Lin, Hao" uniqKey="Lin H" first="Hao" last="Lin">Hao Lin</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.54549.39</institution-id><institution-id institution-id-type="ISNI">0000 0004 0369 4060</institution-id><institution>Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology,</institution><institution>University of Electronic Science and Technology of China,</institution></institution-wrap>Chengdu, 610054 China</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmc">7157830</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7157830</idno><idno type="RBID">PMC:7157830</idno><idno type="doi">10.1007/s12250-020-00221-6</idno><idno type="pmid">NONE</idno><date when="2020">2020</date><idno type="wicri:Area/Pmc/Corpus">000224</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000224</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Computational Identification of Small Interfering RNA Targets in SARS-CoV-2</title><author><name sortKey="Chen, Wei" sort="Chen, Wei" uniqKey="Chen W" first="Wei" last="Chen">Wei Chen</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.411304.3</institution-id><institution-id institution-id-type="ISNI">0000 0001 0376 205X</institution-id><institution>Innovative Institute of Chinese Medicine and Pharmacy,</institution><institution>Chengdu University of Traditional Chinese Medicine,</institution></institution-wrap>Chengdu, 611137 China</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Feng, Pengmian" sort="Feng, Pengmian" uniqKey="Feng P" first="Pengmian" last="Feng">Pengmian Feng</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.411304.3</institution-id><institution-id institution-id-type="ISNI">0000 0001 0376 205X</institution-id><institution>Innovative Institute of Chinese Medicine and Pharmacy,</institution><institution>Chengdu University of Traditional Chinese Medicine,</institution></institution-wrap>Chengdu, 611137 China</nlm:aff></affiliation></author><author><name sortKey="Liu, Kewei" sort="Liu, Kewei" uniqKey="Liu K" first="Kewei" last="Liu">Kewei Liu</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Wu, Meng" sort="Wu, Meng" uniqKey="Wu M" first="Meng" last="Wu">Meng Wu</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</nlm:aff></affiliation></author><author><name sortKey="Lin, Hao" sort="Lin, Hao" uniqKey="Lin H" first="Hao" last="Lin">Hao Lin</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.54549.39</institution-id><institution-id institution-id-type="ISNI">0000 0004 0369 4060</institution-id><institution>Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology,</institution><institution>University of Electronic Science and Technology of China,</institution></institution-wrap>Chengdu, 610054 China</nlm:aff></affiliation></author></analytic><series><title level="j">Virologica Sinica</title><idno type="ISSN">1674-0769</idno><idno type="eISSN">1995-820X</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Bellaousov, S" uniqKey="Bellaousov S">S Bellaousov</name></author><author><name sortKey="Reuter, Js" uniqKey="Reuter J">JS Reuter</name></author><author><name 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sortKey="Sharp, Pa" uniqKey="Sharp P">PA Sharp</name></author><author><name sortKey="Eisen, Hn" uniqKey="Eisen H">HN Eisen</name></author><author><name sortKey="Chen, J" uniqKey="Chen J">J Chen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Huang, C" uniqKey="Huang C">C Huang</name></author><author><name sortKey="Li, M" uniqKey="Li M">M Li</name></author><author><name sortKey="Chen, C" uniqKey="Chen C">C Chen</name></author><author><name sortKey="Yao, Q" uniqKey="Yao Q">Q Yao</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ji, Fm" uniqKey="Ji F">FM Ji</name></author><author><name sortKey="Luo, Lf" uniqKey="Luo L">LF Luo</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Li, T" uniqKey="Li T">T Li</name></author><author><name sortKey="Zhang, Y" uniqKey="Zhang Y">Y Zhang</name></author><author><name sortKey="Fu, L" uniqKey="Fu L">L Fu</name></author><author><name sortKey="Yu, C" uniqKey="Yu C">C Yu</name></author><author><name sortKey="Li, X" uniqKey="Li X">X Li</name></author><author><name sortKey="Li, Y" uniqKey="Li Y">Y Li</name></author><author><name sortKey="Zhang, X" uniqKey="Zhang X">X Zhang</name></author><author><name sortKey="Rong, Z" uniqKey="Rong Z">Z Rong</name></author><author><name sortKey="Wang, Y" uniqKey="Wang Y">Y Wang</name></author><author><name sortKey="Ning, H" uniqKey="Ning H">H Ning</name></author><author><name sortKey="Liang, R" uniqKey="Liang R">R Liang</name></author><author><name sortKey="Chen, W" uniqKey="Chen W">W Chen</name></author><author><name sortKey="Babiuk, La" uniqKey="Babiuk L">LA Babiuk</name></author><author><name sortKey="Chang, Z" uniqKey="Chang Z">Z Chang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nguyen, Tm" uniqKey="Nguyen T">TM Nguyen</name></author><author><name sortKey="Zhang, Y" uniqKey="Zhang Y">Y Zhang</name></author><author><name sortKey="Pandolfi, Pp" uniqKey="Pandolfi P">PP Pandolfi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Phan, T" uniqKey="Phan T">T Phan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Shi, Y" uniqKey="Shi Y">Y Shi</name></author><author><name sortKey="Yang, Dh" uniqKey="Yang D">DH Yang</name></author><author><name sortKey="Xiong, J" uniqKey="Xiong J">J Xiong</name></author><author><name sortKey="Jia, J" uniqKey="Jia J">J Jia</name></author><author><name sortKey="Huang, B" uniqKey="Huang B">B Huang</name></author><author><name sortKey="Jin, Yx" uniqKey="Jin Y">YX Jin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wilson, Ja" uniqKey="Wilson J">JA Wilson</name></author><author><name sortKey="Jayasena, S" uniqKey="Jayasena S">S Jayasena</name></author><author><name sortKey="Khvorova, A" uniqKey="Khvorova A">A Khvorova</name></author><author><name sortKey="Sabatinos, S" uniqKey="Sabatinos S">S 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Virol Sin</journal-id><journal-id journal-id-type="iso-abbrev">Virol Sin</journal-id><journal-title-group><journal-title>Virologica Sinica</journal-title></journal-title-group><issn pub-type="ppub">1674-0769</issn><issn pub-type="epub">1995-820X</issn><publisher><publisher-name>Springer Singapore</publisher-name><publisher-loc>Singapore</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmc">7157830</article-id><article-id pub-id-type="publisher-id">221</article-id><article-id pub-id-type="doi">10.1007/s12250-020-00221-6</article-id><article-categories><subj-group subj-group-type="heading"><subject>Letter</subject></subj-group></article-categories><title-group><article-title>Computational Identification of Small Interfering RNA Targets in SARS-CoV-2</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-6857-7696</contrib-id><name><surname>Chen</surname><given-names>Wei</given-names></name><address><email>greatchen@ncst.edu.cn</email></address><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Feng</surname><given-names>Pengmian</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Liu</surname><given-names>Kewei</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Wu</surname><given-names>Meng</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-6265-2862</contrib-id><name><surname>Lin</surname><given-names>Hao</given-names></name><address><email>hlin@uestc.edu.cn</email></address><xref ref-type="aff" rid="Aff3">3</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.411304.3</institution-id><institution-id institution-id-type="ISNI">0000 0001 0376 205X</institution-id><institution>Innovative Institute of Chinese Medicine and Pharmacy,</institution><institution>Chengdu University of Traditional Chinese Medicine,</institution></institution-wrap>Chengdu, 611137 China</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.440734.0</institution-id><institution-id institution-id-type="ISNI">0000 0001 0707 0296</institution-id><institution>Center for Genomics and Computational Biology, School of Life Sciences,</institution><institution>North China University of Science and Technology,</institution></institution-wrap>Tangshan, 063210 China</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="GRID">grid.54549.39</institution-id><institution-id institution-id-type="ISNI">0000 0004 0369 4060</institution-id><institution>Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology,</institution><institution>University of Electronic Science and Technology of China,</institution></institution-wrap>Chengdu, 610054 China</aff></contrib-group><pub-date pub-type="epub"><day>15</day><month>4</month><year>2020</year></pub-date><fpage>1</fpage><lpage>3</lpage><history><date date-type="received"><day>6</day><month>3</month><year>2020</year></date><date date-type="accepted"><day>3</day><month>4</month><year>2020</year></date></history><permissions><copyright-statement>© Wuhan Institute of Virology, CAS 2020</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions></article-meta></front><body><p id="Par1">Dear Editor,</p><p id="Par2">At the end of 2019, a new virus, called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was reported (Benvenuto <italic>et al.</italic><xref ref-type="bibr" rid="CR2">2020</xref>; Zhu <italic>et al.</italic><xref ref-type="bibr" rid="CR15">2020</xref>). The sequences of SARS-CoV-2 reported by different research groups demonstrated that it is a positive strand RNA virus. The sequence of SARS-CoV-2 is approximately 30 kb long, and could encodes spike, envelope, membrane, nucleocapsid proteins, etc. (Phan <xref ref-type="bibr" rid="CR11">2020</xref>). These proteins are responsible for replicating the viral genome as well as generating nested transcripts that are used in the synthesis of the viral proteins.</p><p id="Par3">As of April 3 2020, there was more than 1 million cases of SARS-COV-2 reported to World Health Organization with 50,000 deaths globally. However, there have been no effective measures to prevent or treat the severe complications caused by SARS-COV-2.</p><p id="Par4">RNA interference (RNAi) is a native and specific post-transcriptional gene silencing mechanism (Bobbin and Rossi <xref ref-type="bibr" rid="CR3">2016</xref>). The progress initiated by double-stranded RNA (dsRNA) to manipulate gene expression (RNAi) has been proved highly effective, at least 10 times more effective than either using sense or antisense RNAs alone (Chalk and Sonnhammer <xref ref-type="bibr" rid="CR4">2002</xref>). The RNAi triggered by dsRNA is a phenomenon of homology-dependent gene silencing and may play certain roles in affecting the process of virus expression and proliferation. Recently, several reports have demonstrated the use of RNAi in blocking virus infection and replication in animal cells (Ge <italic>et al.</italic><xref ref-type="bibr" rid="CR6">2003</xref>), suggesting that the small interfering RNA (siRNA, 21–25 nt long) plays an important role in RNAi-related gene silencing pathways (Elbashir <italic>et al.</italic><xref ref-type="bibr" rid="CR5">2001</xref>). Progress has been made in anti-HIV and anti-HCV drug design by applying the method of RNA interference (Wilson <italic>et al.</italic><xref ref-type="bibr" rid="CR13">2003</xref>). The effectiveness of siRNA for inhibiting SARS coronavirus genes expression was also demonstrated by Shi <italic>et al.</italic> (<xref ref-type="bibr" rid="CR12">2005</xref>). Besides silencing the targeted genes, the siRNAs can also inhibit the replication of the virus. For example, it has been demonstrated that, by targeting the Leader sequence of SARS-CoV, the siRNA demonstrate a strong inhibitory effect on SARS-CoV replication (Li <italic>et al.</italic><xref ref-type="bibr" rid="CR9">2005</xref>). More recently, a CRISPR/Cas13d system was proposed for the treatment of SARS-COV-2 (Nguyen <italic>et al.</italic><xref ref-type="bibr" rid="CR10">2020</xref>). These results indicate that both RNAi and CRISPR/Cas technology might become potential therapeutic approaches for treating viral diseases.</p><p id="Par5">Accordingly, as complementary to the CRISPR/Cas13d system, we proposed an RNAi based strategy that might interfere the gene expression and block the replication of SARS-COV-2. The main idea of this strategy is to search for siRNA targets in the virus genome, which will be recognized and cleaved by the RNA-induced silencing complex (RISC).</p><p id="Par6">In this work, we performed theoretical predictions of the potential siRNA targets in the virus genome. We firstly collected the representative SARS-COV-2 genome (MN908947, <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/nuccore/MN908947">https://www.ncbi.nlm.nih.gov/nuccore/MN908947</ext-link>) and the mutation information of the SARS-COV-2 genomes from the 2019nCoVR database (Zhao <italic>et al.</italic><xref ref-type="bibr" rid="CR14">2020</xref>), which is available at <ext-link ext-link-type="uri" xlink:href="https://bigd.big.ac.cn/ncov/">https://bigd.big.ac.cn/ncov/</ext-link>. The 2019nCoVR database not only integrates genomic and proteomic sequences of SARS-COV-2 from different resources, but also provides a series of scientific services, such as variation visualization, variation annotations, AI diagnosis, etc.</p><p id="Par7">Next, we folded the SARS-COV-2 genome (MN908947) in a window of 3000 nucleotides with the step of 1500 nucleotides by using RNAstructure (version 4.5) program (Bellaousov <italic>et al.</italic><xref ref-type="bibr" rid="CR1">2013</xref>). Only those 21–25 nt long non-base-paired regions can be served as the potential targets of siRNA (Huang <italic>et al.</italic><xref ref-type="bibr" rid="CR7">2008</xref>), which is called free segments. The long non-base-paired region containing one or several short stems (total length of stems 1–3 base pairs), called quasi-free segments (Ji and Luo <xref ref-type="bibr" rid="CR8">2004</xref>), was also considered in the present work.</p><p id="Par8">A given RNA sequence segment may have different configurations of secondary structure with lower free energy. The total frequency of a segment occurring in non-base-paired region of different folds (20 folds are selected for each segment) is called appearance rate (AR). If each quasi-free case is multiplied by a reduced factor in numeration, namely, by 0.9 for 1 base pair, 0.8 for 2 base pair, and 0.7 for 3 base pairs (base pairs may be continuous in structure or disconnected) then the total number of folds is called reduced appearance rate (RAR) (Ji and Luo <xref ref-type="bibr" rid="CR8">2004</xref>).</p><p id="Par9">To guarantee the safety of the designed drug, we further performed alignment of the free and quasi-free segments with human genome (hg 38) by using BLAST and deleted the matching ones in siRNA target candidates.</p><p id="Par10">Finally, we obtained nine potential siRNA targets in the SARS-COV-2 genome (MN908947). The information about their position and region in the virus genome, length, AR and RAR was provided in Table <xref rid="Tab1" ref-type="table">1</xref>.<table-wrap id="Tab1"><label>Table 1</label><caption><p>siRNA target sequence in plus strand of coronavirus (MN908947).</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left">Target 5′–3′</th><th align="left">Position</th><th align="left">Region</th><th align="left">Length</th><th align="left">AR (RAR)</th><th align="left">Number of mutation strain</th></tr></thead><tbody><tr><td align="left">AAUAGUUUAAAAAUUACAG<bold><underline>A</underline></bold>AGA</td><td char="–" align="char">6509–6531</td><td align="left">Orf1ab</td><td align="left">23</td><td align="left">20 (20)</td><td align="left">1</td></tr><tr><td align="left">UCCUUCUUUAGAAACUAUACA</td><td char="–" align="char">7168–7188</td><td align="left">Orf1ab</td><td align="left">21</td><td align="left">18 (12.6)</td><td align="left">0</td></tr><tr><td align="left">UGGUUUCACUACUUUCUGUUU</td><td char="–" align="char">11,997–12,017</td><td align="left">Orf1ab</td><td align="left">21</td><td align="left">15 (10.5)</td><td align="left">0</td></tr><tr><td align="left">UUCACUACUUUCUGUUUUGCU</td><td char="–" align="char">12,001–12,021</td><td align="left">Orf1ab</td><td align="left">21</td><td align="left">15 (10.5)</td><td align="left">0</td></tr><tr><td align="left">AUGUCAUCCCUACUAUAACUCAAA</td><td char="–" align="char">15,041–15,064</td><td align="left">Orf1ab</td><td align="left">24</td><td align="left">18 (18)</td><td align="left">0</td></tr><tr><td align="left">UUAAAAUAUAAUGAAAAUGGA</td><td char="–" align="char">22,391–22,411</td><td align="left">S</td><td align="left">21</td><td align="left">18 (12.6)</td><td align="left">0</td></tr><tr><td align="left">CUUGAAGCCCCUUUUCUCUAUCUUU</td><td char="–" align="char">25,693–25,717</td><td align="left">Orf3a</td><td align="left">25</td><td align="left">18 (12.6)</td><td align="left">0</td></tr><tr><td align="left">CAACUAUAAAUUAAACACA<bold><underline>G</underline></bold>A</td><td char="–" align="char">27,128–27,148</td><td align="left">M</td><td align="left">21</td><td align="left">19 (19)</td><td align="left">2</td></tr><tr><td align="left">UUGAAUACACCAAAAGAUCACAUU</td><td char="–" align="char">28,688–28,711</td><td align="left">N</td><td align="left">24</td><td align="left">18 (18)</td><td align="left">0</td></tr></tbody></table><table-wrap-foot><p>The bold and underlined characters indicate the SNP found in different strains.</p></table-wrap-foot></table-wrap></p><p id="Par11">In addition, we also analyzed the mutations of the target sequences by comparing all the 143 high quality strains in the 2019nCoVR database (as of March 15, 2020). SNP were found in two of the nine target sequences (indicated by bold character in Table <xref rid="Tab1" ref-type="table">1</xref>). For the potential target ‘AAUAGUUUAAAAAUUACAGAAGA’, only one SNP was found in the strain BetaCoV/Wuhan/HBCDC-HB-05/2020, which is a coding_sequence_variant that changes the coding sequence. For ‘CAACUAUAAAUUAAACACAGA’, the SNP was found in the strain BetaCoV/Singapore/6/2020 and BetaCoV/Singapore/2/2020, respectively, which is a missense_variant that changes G to A resulting in a different amino acid sequence. These results indicate that the selected targets are conserved among the existing SARS-COV-2 genomes.</p><p id="Par12">Although there are still some challenges that needed to be overcome for the clinic applications of siRNA, progresses have been made to solve the fundamental problems, such as off-target effects and effective delivery. For example, the position-specific chemical modification of siRNAs could can significantly reduce off targeting; safe and effective <italic>in vivo</italic> delivery systems have also been developed, such as nanoparticles, cationic lipids, antibodies, cholesterol, aptamers delivery strategies. Therefore, we hope that the above results would be useful in drug design and treatments against SARS-COV-2.</p></body><back><ack><title>Acknowledgements</title><p>The authors would like to express gratitude to the Editor and anonymous reviewers for their constructive comments. This work was supported by the National Nature Scientific Foundation of China (31771471, 61772119) and the Natural Science Foundation for Distinguished Young Scholar of Hebei Province (No. C2017209244).</p></ack><notes><title>Compliance with Ethical Standards</title><notes notes-type="COI-statement"><title>Conflict of interest</title><p id="Par13">The authors declare that they have no conflict of interest.</p></notes><notes><title>Animal and Human Rights Statement</title><p id="Par14">This article does not contain any studies with human or animal subjects performed by any of the authors.</p></notes></notes><ref-list id="Bib1"><title>References</title><ref id="CR1"><element-citation publication-type="journal"><person-group 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